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A Single-arm, Prospective, Multi-center Cohort Study Based on Deep Learning-based cfDNA Fragment Omics to Verify the TuFEst Model for the Staging Diagnosis of Breast Cancer Lesions and Lymph Nodes

NCT07304934 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 269

Last updated 2025-12-26

No results posted yet for this study

Summary

Through the research of this project, we expect to achieve the cfDNA fragment omics liquid biopsy technology based on deep learning, verify the accuracy of the TuFEst model in predicting the tumor burden status of breast cancer lesions and lymph nodes in newly diagnosed breast cancer patients and those receiving neoadjuvant therapy, and provide a theoretical basis for large-scale clinical application in the future

Conditions

Interventions

OTHER

No Intervention: Observational Cohort

No Intervention: Observational Cohort

Sponsors & Collaborators

  • Second Affiliated Hospital, School of Medicine, Zhejiang University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
70 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-12-01
Primary Completion
2027-12-31
Completion
2027-12-31

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07304934 on ClinicalTrials.gov